Single particle tracking has seen numerous applications in biophysics, ranging from the diffusion of proteins in cell membranes to the movement of molecular motors. A plethora of computer algorithms have been developed to monitor the sub-pixel displacement of fluorescent objects between successive video frames, and some have been claimed to have "nanometer" resolution. To date, there has been no rigorous comparison of these algorithms under realistic conditions. In this paper, we quantitatively compare specific implementations of four commonly used tracking algorithms: cross-correlation, sum-absolute difference, centroid, and direct Gaussian fit. Images of fluorescent objects ranging in size from point sources to 5 microm were computer generated with known sub-pixel displacements. Realistic noise was added and the above four algorithms were compared for accuracy and precision. We found that cross-correlation is the most accurate algorithm for large particles. However, for point sources, direct Gaussian fit to the intensity distribution is the superior algorithm in terms of both accuracy and precision, and is the most robust at low signal-to-noise. Most significantly, all four algorithms fail as the signal-to-noise ratio approaches 4. We judge direct Gaussian fit to be the best algorithm when tracking single fluorophores, where the signal-to-noise is frequently near 4.

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A cell-scaled microbead system was used to analyze the force-dependent kinetics of P-selectin adhesive bonds independent of micromechanical properties of the neutrophil's surface microvilli, an elastic structure on which P-selectin ligand glycoprotein-1 (PSGL-1) is localized. Microvillus extension has been hypothesized in contributing to the dynamic range of leukocyte rolling observed in vivo during inflammatory processes. To evaluate PSGL-1/P-selectin bond kinetics of microbeads and neutrophils, rolling and tethering on P-selectin-coated substrates were compared in a parallel-plate flow chamber. The dissociation rates for PSGL-1 microbeads on P-selectin were briefer than those of neutrophils for any wall shear stress, and increased more rapidly with increasing flow. The microvillus length necessary to reconcile dissociation constants of PSGL-1 microbeads and neutrophils on P-selectin was 0.21 microm at 0.4 dyn/cm2, and increased to 1.58 microm at 2 dyn/cm2. The apparent elastic spring constant of the microvillus ranged from 1340 to 152 pN/microm at 0.4 and 2.0 dyn/cm2 wall shear stress. Scanning electron micrographs of neutrophils rolling on P-selectin confirmed the existence of micrometer-scaled tethers. Fixation of neutrophils to abrogate microvillus elasticity resulted in rolling behavior similar to PSGL-1 microbeads. Our results suggest that microvillus extension during transient PSGL-1/P-selectin bonding may enhance the robustness of neutrophil rolling interactions.

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Time-delay estimation (TDE) is a common operation in ultrasound signal processing. In applications such as blood flow estimation, elastography, phase aberration correction, and many more, the quality of final results is heavily dependent upon the performance of the time-delay estimator implemented.In the past years, several algorithms have been developed and applied in medical ultrasound, sonar, radar, and other fields. In this paper we analyze the performances of the widely used normalized and non-normalized correlations, along with normalized covariance, sum absolute differences (SAD), sum squared differences (SSD), hybrid-sign correlation, polarity-coincidence correlation, and the Meyr-Spies method. These techniques have been applied to simulated ultrasound radio frequency (RF) data under a variety of conditions. We show how parameters, which include center frequency, fractional bandwidth, kernel window size, signal decorrelation, and signal-to-noise ratio (SNR) affect the quality of the delay estimate. Simulation results also are compared with a theoretical performance limit set by the Cramér-Rao lower bound (CRLB).Results show that, for high SNR, high signal correlation, and large kernel size, all of the algorithms closely match the theoretical bound, with relative performances that vary by as much as 20%. As conditions degrade, the performances of various algorithms differ more significantly. For signals with a correlation level of 0.98, SNR of 30 dB, center frequency of 5 MHz with a fractional bandwidth of 0.5, and kernel size of 2 s, the standard deviation of the jitter error is on the order of few nanoseconds. Normalized correlation, normalized covariance, and SSD have an approximately equal jitter error of 2.23 ns (the value predicted by the CRLB is 2.073 ns), whereas the polarity-coincidence correlation performs less well with a jitter error of 2.74 ns.